LEIBER-X Technology

LEIBER-X™

Single-cell Intelligence as a Service

Accelerate clinical success through cellular-level patient intelligence platform

Transform $50 bulk RNA-seq into $4,000+ single-cell resolution profiles with explainability, reproducibility, and audit trails that validators trust

GRN + CNV Explainability

Gold-standard Reproducibility

Audit-ready Traceability

100K+ Archives Reactivated

<4 Week Pilots

Validator Sign-off

CDx Champion Enablement

3-Tier Pricing

Virtual Cell Architecture

Transforming bulk data into single-cell precision through AI-powered deconvolution

1

Single-Cell Core

Data Foundation

WittGen single-cell database with 1.3B+ cells provides the ground truth for all platform capabilities.

Comprehensive multi-cancer single-cell atlas
Validated cellular profiles across tumor types
High-quality reference data for deconvolution
Single-Cell Core
2

Bulk-to-Single Cell GenAI

Affordable Single-Cell Resolution

Transform $50 bulk RNA-seq into $4,000+ single-cell resolution profiles with cellular-level precision.

GenAI-powered deconvolution of bulk samples
Multimodal single-cell predictions
Cost-effective patient stratification
Bulk-to-Single Cell GenAI
3

Image-to-Omics

Image2SC Capability

Derive single-cell omics insights from imaging data to expand analytical capabilities.

Spatial context integration
Image-based cellular profiling
Complementary to molecular data
Image-to-Omics

Continuous Value Across Clinical Phases

From historical data analysis through trial design, patient screening, and outcome analysis

Historical Data AnalysisTrial DesignPatient ScreeningOutcome Analysis

Superior Data Quality = Superior Results

Our data-centric AI approach prioritizes quality over quantity. Well-curated datasets with precise annotation deliver significantly better model performance.

95% ML Accuracy

vs. 70% market standard

Subtyping
95%
Grade
92%
Cell Composition
98%

Our Competitive Edge

  • CNV inference scoring for cell-level validation
  • Manual expert curation + extra information mining
  • Golden standard reference dataset construction
  • Automated annotation pipeline for scale

UMAP Representation

Real vs Generated Cell Distributions

PDAC (Test Information)

PDAC Real Data UMAP Plot

Real Data

PDAC Generated Data UMAP Plot

Generated Data

PDAC Real vs Generated Data Comparison UMAP Plot

Real vs Generated

Virtual Cell Model maintains high performance in complex cancer datasets, scoring MMD ≈ 0.7 / WD ≈ 10.6

3.4M+
Cancer Cells
From over 468 patients across multiple cancer types
PDAC, HGSOC, SCLC, Breast Cancer, NETs
8.5M+
Normal Cells
From over 933 healthy donors
Ever-expanding through web crawling & automatic annotation

The Virtual Cell GenAI Pipeline

From your bulk RNA archives to regulator-ready patient stratification—here's how our platform transforms your data into actionable insights.

Input

Bulk RNA Archives

$50 runs, FFPE, and historical datasets you already trust. We handle QC, harmonization, PHI guardrails, and metadata normalization automatically.

Virtual Cell GenAI

Output

Regulator-Ready Strat Plans

Single-cell clarity on cohorts, responder predictions, biomarker packages, and documentation that Bioinformatics validators and regulators can sign off on.

What WittGen Delivers

Retrospective Pilot

We convert legacy bulk RNA-seq into single-cell clarity for one priority program, deliver cohort guidance, and prove uplift before you commit to wet-lab.

Validator Evidence Pack

Explainability • Reproducibility • Traceability documentation for Bioinformatics and regulatory reviewers, including GRN/CNV narratives and model cards.

Pipeline Expansion Kit

Playbooks, APIs, and CDx/Innovation champion tooling so you can run multiple programs in parallel (Pipeline + Platform tiers).

3x
Faster Predictions

Virtual patient responses before actual dosing accelerates decision-making.

5x
More Insights

Biomarkers at cellular level (TME/rare cell populations) unlock hidden opportunities.

7x
Boost Success Rates

Identify responder populations with 7x higher precision through cellular-level profiling.

70%
Cost Reduction

$50 bulk RNA-seq achieves 95% savings versus traditional $4,000+ single-cell methods.

See How We Fixed Stratification

Read how innovation teams, CDx partners, and bioinformatics validators aligned on WittGen output before moving to pipeline and platform tiers.

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